hackernews

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly indicates a read-only operation ('Get') and specifies the item types ('story or comment'), but doesn't mention potential errors (e.g., for invalid IDs), rate limits, or authentication needs. It adds basic context but lacks detailed behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the purpose without unnecessary words. Every part earns its place by specifying the action, resource, type, and identification method concisely.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (single parameter, no annotations, no output schema), the description is adequate but has gaps. It covers the basic purpose and parameter intent but lacks details on return values, error handling, or usage nuances, making it minimally viable rather than fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, with the parameter 'id' fully documented in the schema. The description adds minimal value by reiterating 'numeric ID' but doesn't provide additional semantics like ID ranges or examples. Baseline 3 is appropriate as the schema handles most parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Get'), resource ('a single Hacker News item'), and scope ('story or comment') with precise identification method ('by its numeric ID'). It distinguishes from sibling tools like 'get_top_stories' (which retrieves multiple stories) and 'search_hn' (which searches content).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'by its numeric ID,' suggesting this tool is for retrieving known items rather than discovering or searching. However, it doesn't explicitly state when not to use it or name alternatives like 'search_hn' for unknown IDs, leaving some guidance implicit rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches current top stories but doesn't mention any behavioral traits such as rate limits, authentication needs, data freshness, or potential side effects. This leaves significant gaps in understanding how the tool behaves in practice.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the tool's function without any unnecessary words. It's front-loaded with the core purpose, making it highly efficient and easy to parse, with every word earning its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It doesn't address what the tool returns (e.g., story details, format), error conditions, or behavioral aspects like performance or limitations. For a tool with no structured metadata, this minimal description leaves too many contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the 'count' parameter documented as 'Number of top stories to return (default: 10)'. The description doesn't add any meaning beyond this, such as explaining what 'top stories' entails or constraints on the count value. Given the high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get') and resource ('current top stories from Hacker News'), making the tool's purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_item' or 'search_hn', which could provide similar content through different mechanisms, so it doesn't reach the highest score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_item' or 'search_hn'. It lacks context about scenarios where top stories are preferred over search results or specific item retrieval, leaving the agent to infer usage without explicit direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It mentions the Algolia API, hinting at external dependencies, but doesn't disclose rate limits, authentication needs, error handling, or response format. For a search tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It front-loads the core purpose ('Search Hacker News stories') and adds clarifying details ('and other content types', 'using the Algolia search API') concisely. Every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a search operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., list of stories with fields), potential limitations, or error cases. For a tool with 3 parameters and external API reliance, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain search syntax or result ordering). Baseline 3 is appropriate when the schema handles parameter documentation effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Search') and resource ('Hacker News stories (and other content types)'), and mentions the underlying API ('Algolia search API'). It distinguishes from 'get_item' (specific item retrieval) and 'get_top_stories' (predefined ranking) by focusing on query-based search. However, it doesn't explicitly contrast with siblings, keeping it at 4 rather than 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_item' or 'get_top_stories'. It lacks context about scenarios where search is preferable (e.g., finding specific content vs. browsing top stories) or any prerequisites. This leaves the agent without explicit usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.